Data Scientist, Consumer Edge

• The ideal candidate is a technical expert who bridges the gap between raw data and actionable strategy
• You must be a hybrid talent, combining deep statistical rigor and machine learning expertise with strong software engineering fundamentals
• 5+ years of hands-on experience in a data science or machine learning role
• Expert-level proficiency in Python and its core data science libraries
• Advanced proficiency in SQL, including window functions, common table expressions (CTEs), and query optimization
• Deep understanding and practical application of machine learning algorithms (e.g., regression, classification, clustering, tree-based models) and statistical principles (e.g., hypothesis testing, experimental design)
• Proven experience leading projects in at least two of the following areas: location analytics, A/B testing, anomaly detection, or time series forecasting
• Demonstrable experience writing clean, maintainable, and production-ready code, with a strong grasp of software engineering best practices
• Exceptional written and verbal communication skills, with a proven ability to present complex technical information to non-technical stakeholders
• Familiarity with cloud platforms (e.g., GCP, AWS,, Azure) and their associated data and ML services

Desirable

• We are seeking an experienced and solutions-oriented Data Scientist to join our data team and tackle our most complex business challenges. This is a leadership role where you will not only build sophisticated models but also own the full data science lifecycle, from problem definition to stakeholder communication
• You will lead high-impact projects in areas like location analytics, time series forecasting, anomaly detection, and large-scale A/B testing
• A critical part of this role is the ability to document design decisions rigorously and communicate findings effectively to both executive leadership and engineering teams
• Apply advanced geospatial techniques to solve challenging location analytics problems, deriving insights from spatial data
• Design, build, validate, and deploy end-to-end machine learning models for key business problems, including anomaly detection and time series forecasting
• Lead the design, execution, and statistical analysis of complex A/B tests and other experiments to drive and measure marketing activation
• Perform deep-dive exploratory and statistical analyses using advanced SQL and Python to query, manipulate, and model large-scale, complex datasets
• Champion software engineering best practices within the data science workflow, including code reviews, version control (Git), testing, containerization, and reproducibility
• Clearly and proactively document technical design decisions, methodologies, and model limitations to ensure transparency and knowledge sharing
• Translate complex analytical concepts and model outcomes into clear, actionable insights for non-technical audiences and senior leadership
• Mentor junior data scientists and analysts, fostering a culture of technical excellence and continuous learning
• The Location team works at the intersection of Data Science and Software Engineering, using Python, BigQuery, Vertex AI, and Dataflow. Collaboration is cross-functional with Basketview and AI Products teams, bridging data infrastructure and AI applications